Why AI Virtual Assistants (Google Assistant, Alexa, Siri) Are Apps, Not System Integrations

AI virtual assistants like Google Assistant, Amazon Alexa, and Apple Siri are often external applications rather than being fully integrated into the operating system. There are several reasons behind this, but the primary one is the complexity and expense involved in updating system-level code. This article delves into the key factors that influence this decision and discusses the benefits and drawbacks of this approach.

Complexity of System-Level Updates

The process of updating a system-level code, such as the operating system (OS), is a complex and lengthy process. In the case of Android, the OS update process is particularly slow due to the involvement of multiple companies. Google updates the core OS, but manufacturers add their customizations and hardware changes. This process involves extensive testing at various stages.

Here is a simplified breakdown of the Android OS update process:

Google updates the core system code

Manufacturers integrate their customizations and hardware changes

Manufacturers perform extensive testing

ISPs (Internet Service Providers) perform additional testing

Updates are released to users

Each of these stages can take a considerable amount of time, often leading to delays in the final update reaching end-users. This process can be further backlogged due to the numerous stakeholders involved.

Advantages of App-Based Updates

On the other hand, app updates are significantly simpler and faster. When a virtual assistant is an app, Google can push updates directly to the app store without the need for extensive testing and approval by multiple entities. This streamlined process allows for more frequent and timely updates.

Here’s how the app update process works:

Google updates the app

Updates are pushed to the app store

Users receive and install the updates automatically or manually

In contrast to system-level updates, app updates do not require extensive integration testing beyond what is needed for compatibility with the OS. This results in faster and more efficient updates for users, enhancing their experience with the virtual assistant.

Cost and Labor Involved

Updating system-level code is not just a matter of pushing a few lines of code. It requires significant planning, integration testing, and regression testing to ensure that the updates do not break existing functionalities. These processes are extensive and labor-intensive, making them costly.

The complexity of OS updates means that assistant updates can only occur as frequently as the scheduled OS updates. Typically, major OS updates occur every six to twelve months, with critical updates being pushed out more frequently. This means that users might have to wait a long time for new features or bug fixes to be implemented.

Conclusion

In conclusion, the decision to keep AI virtual assistants as apps instead of system integrations is a strategic choice driven by the need for speed, cost-effectiveness, and user experience. While system-level integration might offer some advantages in terms of seamless integration with the OS, the practical challenges and limitations make app-based updates the preferred method for most virtual assistants.

For users, this means faster and more frequent updates, more timely feature releases, and a more responsive and supportable product. However, it also means that certain integration benefits might be sacrificed for the sake of efficiency and ease of use.